Measures of Obesity
Body Mass Index (BMI) is the primary measure used to define and screen for obesity, calculated as weight in kilograms divided by height in meters squared (kg/m²), with obesity defined as a BMI ≥30 kg/m². 1, 2
BMI Calculation and Classification
BMI serves as the standard screening tool for obesity assessment in clinical practice and epidemiological studies. 1
Calculation Methods:
- Metric formula: weight (kg) / height (m)² 1
- Imperial formula: [weight (pounds) / height (inches)²] × 703 1
Standard Classification (Adults):
- Underweight: BMI <18.5 kg/m² 2
- Normal weight: BMI 18.5-24.9 kg/m² 2
- Overweight: BMI 25.0-29.9 kg/m² 1, 2
- Obesity: BMI ≥30.0 kg/m² 1, 2
Ethnic-Specific Considerations:
Asian populations require lower BMI thresholds due to greater adiposity and higher comorbidity risks at lower BMI levels, with overweight defined as BMI ≥23 kg/m² in this population. 1, 2
Strengths of BMI
BMI demonstrates excellent reliability and correlation with body fat:
- Highly correlated with body fat percentage: R² = 0.95 in men; R² = 0.98 in women 1
- Easy to measure and reproducible in clinical settings 1
- Strong prospective links with adverse health outcomes including cardiovascular disease, diabetes, and mortality 1
- Good specificity (90%) for detecting excess adiposity 1
Critical Limitations of BMI
BMI has poor sensitivity (50%) for identifying excess adiposity, missing half of individuals with excess body fat. 1
Key Limitations:
- Does not distinguish between lean and fat mass, potentially misclassifying muscular individuals as overweight 1, 2
- Does not account for body fat distribution, an independent cardiovascular risk factor 1
- Age and sex variations: Women have higher body fat percentages than men at similar BMI levels 1
- Ethnic differences: Hispanic women have higher body fat than Black and White women at similar BMI; Black women have lower body fat than White women at the same BMI 1
- 30-46% of individuals with BMI <30 kg/m² have obesity-level body fat when measured directly 1, 3
Complementary Measures for Central Adiposity
Waist circumference should be measured in addition to BMI to assess central (abdominal) adiposity, which predicts cardiovascular risk independent of BMI. 1, 2
Waist Circumference Thresholds:
- Men: >102 cm (>40 inches) indicates increased cardiovascular risk 2
- Women: >88 cm (>35 inches) indicates increased cardiovascular risk 2
Additional Anthropometric Measures:
- Waist-to-hip ratio: Better predictor of cardiovascular and total mortality than BMI in some populations 1, 2
- Waist-to-height ratio: Useful for identifying metabolic abnormalities 2
Central adiposity measured by waist circumference predicted cardiovascular mortality in older men (≥65 years) when BMI showed no relationship with mortality. 1
Pediatric Considerations
Children require age- and sex-specific BMI percentiles rather than absolute BMI cutoffs used in adults. 4
Pediatric Classification:
- Overweight: BMI 85th-94th percentile for age and sex 4
- Obesity: BMI ≥95th percentile for age and sex 4
- Severe obesity: BMI ≥120% of the 95th percentile 4
Rapid changes in body composition during growth make obesity assessment more complex in children than adults, requiring age-adjusted reference values. 1, 4
Clinical Application Algorithm
For Adults:
- Calculate BMI using weight and height 1
- If BMI ≥30 kg/m²: Obesity is confirmed; proceed to risk assessment 1, 2
- If BMI 25-29.9 kg/m²: Measure waist circumference to assess central adiposity 1, 2
- If BMI <25 kg/m² but clinical suspicion exists: Consider direct body fat measurement, as BMI misses significant numbers of individuals with excess adiposity 1, 3
- For Asian patients: Apply lower thresholds (BMI ≥23 kg/m² for overweight) 1, 2
Common Pitfalls:
- Relying solely on BMI without measuring waist circumference misses individuals with high-risk central adiposity 1
- Using BMI alone in elderly patients, where it correlates less strongly with body fat percentage 1
- Applying adult BMI cutoffs to children, who require percentile-based assessment 4
- Ignoring ethnic-specific differences in body composition and disease risk 1, 2